### Resumé

Originalsprog | Engelsk |
---|---|

Titel | System Modelling and Optimization : Proceedings of the 11th IFIP Conference |

Redaktører | Palle Thoft-Christensen |

Antal sider | 10 |

Forlag | Springer |

Publikationsdato | 1984 |

Sider | 585-594 |

ISBN (Trykt) | 3-540-13185-X |

Status | Udgivet - 1984 |

Begivenhed | System Modelling and Optimization: IFIP - København, Danmark Varighed: 25 jul. 1983 → 29 jul. 1983 Konferencens nummer: 11 |

### Konference

Konference | System Modelling and Optimization |
---|---|

Nummer | 11 |

Land | Danmark |

By | København |

Periode | 25/07/1983 → 29/07/1983 |

Navn | Lecture Notes in Control and Information Sciences |
---|---|

Vol/bind | 59 |

ISSN | 0170-8643 |

### Fingerprint

### Emneord

- Bilinear Hysteretic Systems
- Structural Reliability
- Physical Uncertainty
- Statistical Uncertainty
- Model Uncertainty

### Citer dette

*System Modelling and Optimization : Proceedings of the 11th IFIP Conference*(s. 585-594). Springer. Lecture Notes in Control and Information Sciences, Bind. 59

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*System Modelling and Optimization : Proceedings of the 11th IFIP Conference.*Springer, Lecture Notes in Control and Information Sciences, bind 59, s. 585-594, System Modelling and Optimization, København, Danmark, 25/07/1983.

**Model Uncertainty for Bilinear Hysteretic Systems.** / Sørensen, John Dalsgaard; Thoft-Christensen, Palle.

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

TY - GEN

T1 - Model Uncertainty for Bilinear Hysteretic Systems

AU - Sørensen, John Dalsgaard

AU - Thoft-Christensen, Palle

PY - 1984

Y1 - 1984

N2 - In structural reliability analysis at least three types of uncertainty must be considered, namely physical uncertainty, statistical uncertainty, and model uncertainty (see e.g. Thoft·Christensen & Baker [1)). The physical uncertainty is usually modelled by a number of basic variables. The statistical uncertainty -due to lack of information can e.g. be taken into account by describing the variables by predictive density functions, Veneziano [2). In general, model uncertainty is the uncertainty connected with mathematical modelling of the physical reality. When structural reliability analysis is related to the concept of a failure surface (or limit state surface) in the n-dimensional basic variable space then model uncertainty is at least due to the neglected variables, the modelling of the failure surface and the computational technique used. A more precise definition is given in section 2, where some different methods to treat model uncertainty are described. In section 3 a new method based on subjectively modelled conditional density functions is presented. It is shown that in some special cases this method is equivalent to existing more simple methods. In the analysis of dynamically loaded structures it is often assumed that the loading and the response can be modelled by stationary stochastic processes. Further, it is assumed that the structures can be modelled by non-linear systems showing hysteresis. This non-linear behaviour is essential to the design procedure from an economic and reliability point of view. In section 4 it is shown how the probability of failure of a simple bilinear oscillator can be estimated and in section 5 it is demonstrated by numerical examples how model uncertainty can be included in the calculations.

AB - In structural reliability analysis at least three types of uncertainty must be considered, namely physical uncertainty, statistical uncertainty, and model uncertainty (see e.g. Thoft·Christensen & Baker [1)). The physical uncertainty is usually modelled by a number of basic variables. The statistical uncertainty -due to lack of information can e.g. be taken into account by describing the variables by predictive density functions, Veneziano [2). In general, model uncertainty is the uncertainty connected with mathematical modelling of the physical reality. When structural reliability analysis is related to the concept of a failure surface (or limit state surface) in the n-dimensional basic variable space then model uncertainty is at least due to the neglected variables, the modelling of the failure surface and the computational technique used. A more precise definition is given in section 2, where some different methods to treat model uncertainty are described. In section 3 a new method based on subjectively modelled conditional density functions is presented. It is shown that in some special cases this method is equivalent to existing more simple methods. In the analysis of dynamically loaded structures it is often assumed that the loading and the response can be modelled by stationary stochastic processes. Further, it is assumed that the structures can be modelled by non-linear systems showing hysteresis. This non-linear behaviour is essential to the design procedure from an economic and reliability point of view. In section 4 it is shown how the probability of failure of a simple bilinear oscillator can be estimated and in section 5 it is demonstrated by numerical examples how model uncertainty can be included in the calculations.

KW - Bilinear Hysteretic Systems

KW - Structural Reliability

KW - Physical Uncertainty

KW - Statistical Uncertainty

KW - Model Uncertainty

KW - Bilinea Hysteretic Systems

KW - Structural Reliability

KW - Physical Uncertainty

KW - Statistical Uncertainty

KW - Model Uncertainty

M3 - Article in proceeding

SN - 3-540-13185-X

SP - 585

EP - 594

BT - System Modelling and Optimization

A2 - Thoft-Christensen, Palle

PB - Springer

ER -